






"""simple docstring"""





import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    FEATURE_EXTRACTOR_MAPPING,
    AutoConfig,
    AutoFeatureExtractor,
    WavaVecaConfig,
    WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / '''utils'''))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


_SCREAMING_SNAKE_CASE   :							int          =		get_tests_dir('''fixtures''')
_SCREAMING_SNAKE_CASE   :							str          =		get_tests_dir('''fixtures/dummy_feature_extractor_config.json''')
_SCREAMING_SNAKE_CASE   :							Tuple          =		get_tests_dir('''fixtures/dummy-config.json''')






class 	a		(   unittest.TestCase						):






    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						Optional[Any]:
      lowerCamelCase_       	=		0






    def   UpperCamelCase			(			self	:				List[str]   )	->						List[str]:
      lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained('facebook/wav2vec2-base-960h'   )
      self.assertIsInstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						Dict:
      lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE   )
      self.assertIsInstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				List[Any]   )	->						Optional[int]:
      with tempfile.TemporaryDirectory() as tmpdirname:
        lowerCamelCase_       	=		WavaVecaConfig()

        # remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE   ).to_dict()

        config_dict.pop('feature_extractor_type'   )
        lowerCamelCase_       	=		WavaVecaFeatureExtractor(**__SCREAMING_SNAKE_CASE   )

        # save in new folder
        model_config.save_pretrained(__SCREAMING_SNAKE_CASE   )
        config.save_pretrained(__SCREAMING_SNAKE_CASE   )

        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE   )

        # make sure private variable is not incorrectly saved
        lowerCamelCase_       	=		json.loads(config.to_json_string()   )
        self.assertTrue('_processor_class' not in dict_as_saved   )

      self.assertIsInstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				Dict   )	->						List[str]:
      lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE   )
      self.assertIsInstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				Union[str, Any]   )	->						Any:
      with self.assertRaisesRegex(
          __SCREAMING_SNAKE_CASE			,		'bert-base is not a local folder and is not a valid model identifier'   ):
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained('bert-base'   )






    def   UpperCamelCase			(			self	:				Dict   )	->						List[Any]:
      with self.assertRaisesRegex(
          __SCREAMING_SNAKE_CASE			,		r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'   ):
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE			,		revision='aaaaaa'   )






    def   UpperCamelCase			(			self	:				Union[str, Any]   )	->						Dict:
      with self.assertRaisesRegex(
          __SCREAMING_SNAKE_CASE			,		'hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'			,		):
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained('hf-internal-testing/config-no-model'   )






    def   UpperCamelCase			(			self	:				int   )	->						Tuple:
      # If remote code is not set, we will time out when asking whether to load the model.
      with self.assertRaises(__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(
            'hf-internal-testing/test_dynamic_feature_extractor'   )
      # If remote code is disabled, we can't load this config.
      with self.assertRaises(__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(
            'hf-internal-testing/test_dynamic_feature_extractor'			,		trust_remote_code=__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(
          'hf-internal-testing/test_dynamic_feature_extractor'			,		trust_remote_code=__SCREAMING_SNAKE_CASE   )
      self.assertEqual(feature_extractor.__class__.__name__			,		'NewFeatureExtractor'   )

      # Test feature extractor can be reloaded.
      with tempfile.TemporaryDirectory() as tmp_dir:
        feature_extractor.save_pretrained(__SCREAMING_SNAKE_CASE   )
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE			,		trust_remote_code=__SCREAMING_SNAKE_CASE   )
      self.assertEqual(reloaded_feature_extractor.__class__.__name__			,		'NewFeatureExtractor'   )






    def   UpperCamelCase			(			self	:				List[str]   )	->						str:
      try:
        AutoConfig.register('custom'			,		__SCREAMING_SNAKE_CASE   )
        AutoFeatureExtractor.register(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )
        # Trying to register something existing in the Transformers library will raise an error
        with self.assertRaises(__SCREAMING_SNAKE_CASE   ):
          AutoFeatureExtractor.register(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )

        # Now that the config is registered, it can be used as any other config with the auto-API
        lowerCamelCase_       	=		CustomFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE   )
        with tempfile.TemporaryDirectory() as tmp_dir:
          feature_extractor.save_pretrained(__SCREAMING_SNAKE_CASE   )
          lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(__SCREAMING_SNAKE_CASE   )
          self.assertIsInstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )

      finally:
        if "custom" in CONFIG_MAPPING._extra_content:
          del CONFIG_MAPPING._extra_content["custom"]
        if CustomConfig in FEATURE_EXTRACTOR_MAPPING._extra_content:
          del FEATURE_EXTRACTOR_MAPPING._extra_content[CustomConfig]






    def   UpperCamelCase			(			self	:				int   )	->						str:






      class 	a		(   __snake_case						):
          SCREAMING_SNAKE_CASE		:	Any		=					True

      try:
        AutoConfig.register('custom'			,		__SCREAMING_SNAKE_CASE   )
        AutoFeatureExtractor.register(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )
        # If remote code is not set, the default is to use local
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(
            'hf-internal-testing/test_dynamic_feature_extractor'   )
        self.assertEqual(feature_extractor.__class__.__name__			,		'NewFeatureExtractor'   )
        self.assertTrue(feature_extractor.is_local   )

        # If remote code is disabled, we load the local one.
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(
            'hf-internal-testing/test_dynamic_feature_extractor'			,		trust_remote_code=__SCREAMING_SNAKE_CASE   )
        self.assertEqual(feature_extractor.__class__.__name__			,		'NewFeatureExtractor'   )
        self.assertTrue(feature_extractor.is_local   )

        # If remote is enabled, we load from the Hub
        lowerCamelCase_       	=		AutoFeatureExtractor.from_pretrained(
            'hf-internal-testing/test_dynamic_feature_extractor'			,		trust_remote_code=__SCREAMING_SNAKE_CASE   )
        self.assertEqual(feature_extractor.__class__.__name__			,		'NewFeatureExtractor'   )
        self.assertTrue(not hasattr(__SCREAMING_SNAKE_CASE			,		'is_local'   )   )

      finally:
        if "custom" in CONFIG_MAPPING._extra_content:
          del CONFIG_MAPPING._extra_content["custom"]
        if CustomConfig in FEATURE_EXTRACTOR_MAPPING._extra_content:
          del FEATURE_EXTRACTOR_MAPPING._extra_content[CustomConfig]












"""simple docstring"""





def 	lowerCamelCase__			(				_lowerCamelCase			:						list[list[int | float]]					) ->							int:
  lowerCamelCase_       	=		len(_lowerCamelCase					)
  lowerCamelCase_       	=		len(matrix[0]					)
  lowerCamelCase_       	=		min(_lowerCamelCase						,							_lowerCamelCase					)

  for row in range(_lowerCamelCase					):
    # Check if diagonal element is not zero
    if matrix[row][row] != 0:
      # Eliminate all the elements below the diagonal
      for col in range(row + 1						,							_lowerCamelCase					):
        lowerCamelCase_       	=		matrix[col][row] / matrix[row][row]
        for i in range(_lowerCamelCase						,							_lowerCamelCase					):
          matrix[col][i] -= multiplier * matrix[row][i]
    else:
      # Find a non-zero diagonal element to swap rows
      lowerCamelCase_       	=		True
      for i in range(row + 1						,							_lowerCamelCase					):
        if matrix[i][row] != 0:
          lowerCamelCase_	,      lowerCamelCase_       	=		matrix[i], matrix[row]
          lowerCamelCase_       	=		False
          break
      if reduce:
        rank -= 1
        for i in range(_lowerCamelCase					):
          lowerCamelCase_       	=		matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
      row -= 1

  return rank


if __name__ == "__main__":
  import doctest

  doctest.testmod()




